Results 11 to 20 of about 259,269 (327)
Dynamic Contextualized Word Embeddings [PDF]
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021 Static word embeddings that represent words by a single vector cannot capture the variability of word meaning in different linguistic and extralinguistic contexts. Building on prior work on contextualized and dynamic word embeddings, we introduce dynamic contextualized word embeddings that represent words as a function of both linguistic and ...
Hofmann, V +2 more
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Morphological Word-Embeddings [PDF]
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2015 Published at NAACL ...
Cotterell, Ryan, Schütze, Hinrich
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Relational Word Embeddings [PDF]
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019 While word embeddings have been shown to implicitly encode various forms of attributional knowledge, the extent to which they capture relational information is far more limited. In previous work, this limitation has been addressed by incorporating relational knowledge from external knowledge bases when learning the word embedding.
Camacho Collados, Jose +2 more
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Creating Welsh Language Word Embeddings [PDF]
Applied Sciences, 2021 Word embeddings are representations of words in a vector space that models semantic relationships between words by means of distance and direction. In this study, we adapted two existing methods, word2vec and fastText, to automatically learn Welsh word embeddings taking into account syntactic and morphological idiosyncrasies of this language.
Padraig Corcoran +4 more
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Name Entity Recognition for Military Based on Domain Adaptive Embedding [PDF]
Jisuanji kexue, 2022 In order to solve the poor quality problem of domain embedding space caused by inadequate military corpus which makes low accuracy of applying deep neural network model to military named entity recognition,this paper introduces a domain adaptive method ...
LIU Kai, ZHANG Hong-jun, CHEN Fei-qiong
doaj +1 more source
Sentence model based subword embeddings for a dialog system
ETRI Journal, 2022 This study focuses on improving a word embedding model to enhance the performance of downstream tasks, such as those of dialog systems. To improve traditional word embedding models, such as skip-gram, it is critical to refine the word features and expand
Euisok Chung +2 more
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All Word Embeddings from One Embedding [PDF]
, 2020 NeurIPS ...
Sho Takase, Shunsuke Kobayashi
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Joint Fine-Grained Components Continuously Enhance Chinese Word Embeddings
IEEE Access, 2019 The most common method of word embedding is to learn word vector representations from context information of large-scale text. However, Chinese words usually consist of characters, subcharacters, and strokes, and each part contains rich semantic ...
Chengyang Zhuang +3 more
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Evaluating the Underlying Gender Bias in Contextualized Word Embeddings [PDF]
, 2019 Gender bias is highly impacting natural language processing applications. Word embeddings have clearly been proven both to keep and amplify gender biases that are present in current data sources.
Basta, Christine +2 more
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Using Word Embedding to Evaluate the Coherence of Topics from Twitter Data [PDF]
, 2016 Scholars often seek to understand topics discussed on Twitter using topic modelling approaches. Several coherence metrics have been proposed for evaluating the coherence of the topics generated by these approaches, including the pre-calculated ...
Fang, Anjie +3 more
core +1 more source